Review Based Service Recommendation for Big Data

Success of web 2.0 brings online information overload. An exponential growth of customers, services and online information has been observed in last decade. It yields big data investigation problem for service recommendation system. Traditional recommender systems often put up with scalability, lack of security and efficiency problems. Users preferences are almost ignored. So, the requirement of robust recommendation system is enhanced now a days. In this paper, we present review based service recommendation to dynamically recommend services to the users. Keywords are extracted from passive users reviews and a rating value is given to every new keyword observed in the dataset. Sentiment analysis is performed on these rating values and top-k services recommendation list is provided to users. To make the system more effective and robust hadoop framework is used.